CNT‐Supported RuNi Composites Enable High Round‐Trip Efficiency in Regenerative Fuel Cells

Regenerative fuel cells hold significant potential for efficient, large-scale energy storage by reversibly converting electrical energy into hydrogen and vice versa, making them essential for leveraging intermittent renewable energy sources. However, their practical implementation is hindered by the unsatisfactory efficiency. Addressing this challenge requires the development of cost-effective electrocatalysts. In this study, a carbon nanotube (CNT)-supported RuNi composite with low Ru loading is developed as an efficient and stable catalyst for alkaline hydrogen and oxygen electrocatalysis, including hydrogen evolution, oxygen evolution, hydrogen oxidation, and oxygen reduction reaction. Furthermore, a regenerative fuel cell using this catalyst composite is assembled and evaluated under practical relevant conditions. As anticipated, the system exhibits outstanding performance in both the electrolyzer and fuel cell modes. Specifically, it achieves a low cell voltage of 1.64 V to achieve a current density of 1 A cm<sup>-</sup> <sup>2</sup> for the electrolyzer mode and delivers a high output voltage of 0.52 V at the same current density in fuel cell mode, resulting in a round-trip efficiency (RTE) of 31.6% without further optimization. The multifunctionality, high activity, and impressive RTE resulted by using the RuNi catalyst composites underscore its potential as a single catalyst for regenerative fuel cells.

Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2025-03-20
DOI
https://doi.org/10.1002/adma.202500416
Citations
3
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
1.09

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CNT‐Supported RuNi Composites Enable High Round‐Trip Efficiency in Regenerative Fuel Cells

Haozhou Yang, Jinzhan Su, Lubing Li, Bin Liu et al.
3 citations
Advanced Materials
Electrocatalysts for Energy Conversion
1.09
article

CNT‐Supported RuNi Composites Enable High Round‐Trip Efficiency in Regenerative Fuel Cells

Haozhou Yang, Jinzhan Su, Lubing Li, Bin Liu, Lei Wang, Yan Zhang, Chunfeng Li, Danning Li
article en
3 citations

Abstract

Regenerative fuel cells hold significant potential for efficient, large-scale energy storage by reversibly converting electrical energy into hydrogen and vice versa, making them essential for leveraging intermittent renewable energy sources. However, their practical implementation is hindered by the unsatisfactory efficiency. Addressing this challenge requires the development of cost-effective electrocatalysts. In this study, a carbon nanotube (CNT)-supported RuNi composite with low Ru loading is developed as an efficient and stable catalyst for alkaline hydrogen and oxygen electrocatalysis, including hydrogen evolution, oxygen evolution, hydrogen oxidation, and oxygen reduction reaction. Furthermore, a regenerative fuel cell using this catalyst composite is assembled and evaluated under practical relevant conditions. As anticipated, the system exhibits outstanding performance in both the electrolyzer and fuel cell modes. Specifically, it achieves a low cell voltage of 1.64 V to achieve a current density of 1 A cm<sup>-</sup> <sup>2</sup> for the electrolyzer mode and delivers a high output voltage of 0.52 V at the same current density in fuel cell mode, resulting in a round-trip efficiency (RTE) of 31.6% without further optimization. The multifunctionality, high activity, and impressive RTE resulted by using the RuNi catalyst composites underscore its potential as a single catalyst for regenerative fuel cells.

Advanced MaterialsVol. 37(18)
National University of Singapore (SG), Xi'an Jiaotong University (CN)
National Research Foundation, Agency for Science, Technology and Research, National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 25%
Electrocatalysts for Energy Conversion
1.09
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.